AB1442 A PREDICTIVE MODEL OF CATASTROPHIC ANTIPHOSPHOLIPID SYNDROME: A RETROSPECTIVE COHORT STUDY
Authors: C. Huang, Y. Zhao, J. Zhao, M. Li, X. Zeng
Journal: Annals of the Rheumatic Diseases (2022)

Background Catastrophic antiphospholipid syndrome (CAPS) is a life-threatening form of antiphospholipid syndrome (APS), with rarely occurrence but high mortality. Current classification diagnosis criteria require more than 3 organs involvement in 1-week time and pathological evidence in patient with persistent positive antiphospholipid antibodies (aPL), which could result the delaying diagnosis and treatment. A predictive model could help identify CAPS patients earlier and initiate early intervention. Objectives To develop a predictive model of CAPS in APS patients in a single-center prospective APS cohort. Methods Data of consecutive APS patients referred into Peking Union Medical College Hospital from May 2013 to October 2021 was collected. A binary logistic regression method was used to identify predictors of CAPS, coefficient B was assigned with score value in the development of prediction model, and risk-stratification was based on the calculated score using the predictive model. The performance of the model was assessed by Nagelkerke’s R 2 , Hosmer-Lemeshow test, Omnibus test, and area under the receiver operating characteristic curve (AUC). Results A total of 27 CAPS (11.9%) occurred in 226 APS patients. CAPS were more likely to occur in male secondary APS patients with history of arterial thrombosis. Precipitating factors (OR 108.961, 95% CI 23.299 to 509.572), thrombocytopenia (OR 14.765, 95% CI 3.088 to 70.612) and elevated serum creatine (OR 5.339, 95% CI 1.301 to 21.907) were selected by the binary logistic regression. The scores of precipitating factors, thrombocytopenia and elevated serum creatine were 5, 3 and 2. The risk scores were divided into high-risk (7-10) and low-risk (0-6), the risk for CAPS were 73.3% and 2.6%, with sensitivity of 81.5% and specificity of 96%. The Nagelkerke’s R 2 (0.696), the Hosmer-Lemeshow test (χ2 =2.192, df=4, p=0.701) and the Omnibus test (χ2 =101.307, df=3, p=0.000) indicated the logistic regression model has a good fit. The AUC was 0.969 (95% CI 0.947 to 0.991, SE=0.011, p=0.000) indicated the model has good discrimination. Conclusion A predictive model of CAPS was developed with precipitating factors, thrombocytopenia, and elevated serum creatine. This model helps physicians identify CAPS in high-risk patients, could achieve early intervention and improve prognosis. Table 1. Characteristics and predicting factors of CAPS in PUMCH-APS cohort CAPS（N=27） Non-CAPS（N=199） p Odds ratio p Coefficient Β Score Gender（M） 14(51.9) 64(32.2) 0.043 Age (y) 36.3±15.2 36.2±12.5 0.975 Disease duration (m) 49.7±77.7 53.9±72.3 0.777 Secondary APS 14(51.9) 52(26.1) 0.006 APS diagnosis Venous thrombosis 17(63.0) 106(53.3) 0.342 Arterial thrombosis 22(81.5) 79(39.7) 0.000 Pregnancy morbidity 5(18.5) 68(34.2) 0.103 LA 22(81.5) 155(77.9) 0.671 aCL 21(77.8) 123(61.8) 0.105 a-β2GP1 23(85.2) 155(77.9) 0.384 Precipitating factors 24(88.9 ) 19(9.5 ) 0.000 108.961(23.299-509.572 ) 0.000 4.691 5 WBC(×10 9 /L) 9.0±6.3 6.6±2.9 0.067 HGB(g/L) 82.7±20.4 130±23.8 0.000 Hemolytic anemia 15(55.6) 20(10.1) 0.000 PLT(×10 9 /L) 61.1±67.1 132±84.0 0.000 Thrombocytopenia 24(88.9 ) 80(40.2 ) 0.000 14.765(3.088-70.612 ) 0.001 2.692 3 Cr(μmol/L) 224.5±225.8 74.4±28.4 0.002 Elevated Cr 15(55.6 ) 34(17.1 ) 0.000 5.339(1.301-21.07 ) 0.020 1.675 2 LDH(U/L) 476.4±227.0 226.9±92.3 0.000 Elevated LDH 25(92.6) 54(27.1) 0.000 Proteinuria 18(66.7) 28(14.1) 0.000 Hematuria 15(55.6) 20(10.1) 0.000 Figure 1. (A). Receiver Operating Characteristic (ROC) curve of the predictive model. Area under the receiver operating characteristic curve (AUC) was 0.969, the cut-off value of 7 were with sensitivity of 81.5% and specificity of 96%. (B). Calibration curve in internal validation. Disclosure of Interests None declared